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作物学报 ›› 2023, Vol. 49 ›› Issue (8): 2196-2209.doi: 10.3724/SP.J.1006.2023.21054

• 耕作栽培·生理生化 • 上一篇    下一篇

冬小麦对水分胁迫响应的模型模拟与节水滴灌制度优化

杨晓慧(), 王碧胜(), 孙筱璐, 侯靳锦, 徐梦杰, 王志军, 房全孝()   

  1. 青岛农业大学农学院, 山东青岛 266109
  • 收稿日期:2022-08-08 接受日期:2023-02-21 出版日期:2023-08-12 网络出版日期:2023-03-03
  • 通讯作者: 王碧胜,房全孝
  • 作者简介:E-mail: yangxiaohui0529@163.com
  • 基金资助:
    国家自然科学基金项目(31671627);山东省自然科学基金青年项目(ZR2021QC113);青岛农业大学博士启动基金项目(6631120069)

Modeling the response of winter wheat to deficit drip irrigation for optimizing irrigation schedule

YANG Xiao-Hui(), WANG Bi-Sheng(), SUN Xiao-Lu, HOU Jin-Jin, XU Meng-Jie, WANG Zhi-Jun, FANG Quan-Xiao()   

  1. College of Agriculture, Qingdao Agricultural University, Qingdao 266109, Shandong, China
  • Received:2022-08-08 Accepted:2023-02-21 Published:2023-08-12 Published online:2023-03-03
  • Contact: WANG Bi-Sheng,FANG Quan-Xiao
  • Supported by:
    National Natural Science Foundation of China(31671627);Youth Program of Shandong Provincial Natural Science Foundation(ZR2021QC113);Qingdao Agricultural University Doctoral Start-up Fund(6631120069)

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摘要：

滴灌技术结合节水灌溉制度可显著提高作物水分利用效率, 但针对滴灌条件下冬小麦节水灌溉制度的优化研究相对较少, 利用作物模型优化节水灌溉制度可以弥补田间试验的不足, 对于作物精确灌溉具有重要的指导意义。本研究利用胶东冬小麦滴灌节水试验数据(2016—2019年)评价了根区水质模型(RZWQM-CERES)的适应性, 并模拟评价了不同节水滴灌制度对冬小麦产量和水分利用效率的影响, 以筛选最佳节水滴灌制度。结果表明RZWQM- CERES可以较好地模拟土壤水分、冬小麦生长和产量对不同滴灌处理和季节的响应, 其中模拟0~90 cm土壤贮水量的均方根误差(RMSE)为22.7~32.3 mm、相对均方根误差(NRMSE)为11.9%~16.3%、决定系数(R2)为0.52~0.69, 模拟收获期生物量的RMSE为1184~1904 kg hm-2、NRMSE为9.9%~16.8%、R2为0.67, 模拟产量的RMSE为361~491 kg hm-2、NRMSE为5.7%~7.8%、R2为0.75。长期模拟结果表明该地区冬小麦需水关键期为孕穗期(丰水年和平水年)或拔节期(枯水年)。针对不同降水年型冬小麦产量和水分利用效率对灌溉量的响应差异, 筛选滴灌条件下冬小麦最佳灌溉制度为: 丰水年在拔节期和开花期各灌水45 mm; 平水年(或枯水年)在拔节期、孕穗期及开花期各灌水35 mm (或45 mm)。本研究结果扩展了RZWQM-CERES优化冬小麦滴灌制度的应用潜力, 为实施冬小麦精确灌溉提供了重要的技术支持。

关键词: 冬小麦, 水分胁迫, 滴灌, 灌溉制度, RZWQM-CERES, 作物产量, 水分利用效率

Abstract:

Combining drip irrigation and water-saving irrigation can increase crop use efficiency greatly, however, few studies investigated water-saving irrigation schedule for winter wheat under drip irrigation conditions. Using crop models to optimize water-saving irrigation systems can make up for the shortcomings of field trials, which can provide the guideline for precise irrigation. In this study, we evaluated the adaptability of the Root Zone Water Quality Model and Crop Estimation through Resource and Environment Synthesis (RZWQM-CERES) using the data from a three-year experiment with drip irrigation water conservation for winter wheat at Jiaodong area. Then we evaluated the influences of different water-saving drip irrigation schedules on winter wheat yield and water use efficiency. The results showed that RZWQM-CERES could effectively simulate the responses of soil moisture, winter wheat growth, and yield to different irrigation treatments and seasons. Root mean square error (RMSE), relative root mean square error (NRMSE), and coefficient of determination (R2) for the simulated soil water storage in 0-90 cm layer were 22.7-32.3 mm, 11.9%-16.3%, and 0.52-0.69, respectively. RMSE, NRMSE, and R2 values for simulated harvest above-ground biomass were 1184-1904 kg hm-2, 9.9%-16.8%, and 0.67, respectively. The corresponding values for simulated grain yield were 361-491 kg hm-2, 5.7%-7.8%, and 0.75, respectively. The long-term simulation results revealed that the critical water requirement period of winter wheat in this region was the booting period (in wet years and normal years) or the jointing period (in dry years). According to the different responses of winter wheat yield and water use efficiency to irrigation amounts and timings among the different rainfall patterns, the recommended optimal drip irrigation regimes for winter wheat at this region were 45 mm irrigation at both jointing and flowering stages in wet years, and 35 mm (or 45 mm) irrigations at the jointing, booting, and flowering stages in normal years (or dry years). These simulation results extended RZWQM-CERES to optimize drip irrigation schedule of winter wheat and provided an important technical support for the implementation of precise irrigation for winter wheat in the region.

Key words: winter wheat, water stress, drip irrigation, irrigation schedule, RZWQM-CERES, crop yield, water use efficiency

图1

2016-2019年冬小麦生育期内逐日(a)最高气温(Tmax)和最低气温(Tmin), (b)太阳辐射量及(c)降雨量"

表1

胶州试验站土壤水力学参数的校正结果"

层次
Soil layer
(cm)		 类型
Soil type		 容重
Bulk density
(g cm-3)		 饱和导水率
Saturated hydraulic conductivity
(cm h-1)		 田间持水量
Field water capacity at 33 kPa
(cm3 cm-3)
0-3 壤质沙土 Loamy sand 1.49 1.94 (1.52-3.36) 0.20 (0.15-0.32)
3-18 壤土 Loam 1.42 1.52 (1.24-2.98) 0.25 (0.15-0.30)
18-55 粉质壤土 Silty loam 1.42 1.52 (1.28-2.75) 0.29 (0.18-0.35)
55-100 黏质壤土 Clay loam 1.42 1.25 (0.85-2.15) 0.28 (0.20-0.35)
100-150 粉质黏壤土 Silty clay loam 1.32 0.39 (0.14-1.35) 0.31 (0.25-0.35)
150-200 粉质黏壤土 Silty clay loam 1.42 0.19 (0.12-0.44) 0.33 (0.25-0.40)

表2

RZWQM-CERES模型冬小麦遗传参数校正结果"

作物参数
Crop parameter		 参数值
Parameter value		 校正范围
Value
range
春化作用特性参数 P1V (d) 30 25-60
光周期特性参数 P1D (%) 30 20-50
灌浆期特性参数 P5 (℃ d) 560 400-650
籽粒数特性参数 G1 (gain g-1) 28 20-45
潜在灌浆速率参数 G2 (mg d-1) 30 20-45
花期潜在单茎穗重参数 G3 (g) 1.3 0.5-2.5
出叶间隔特性参数 PHINT (℃) 80 70-90

图2

2016-2019年RZWQM-CERES模拟不同灌溉处理下0~90 cm土壤贮水量(mm)与实测值对比"

表3

2016-2019年RZWQM-CERES模拟不同灌溉处理下0~90 cm土壤贮水量、收获期生物量、产量及农田蒸散量与观测值对比"

项目
Item		 处理
Treatment		 观测值
Measured		 模拟值
Simulated		 相对误差
MRE (%)		 决定系数
R2		 均方根
误差
RMSE		 相对均方根
误差
NRMSE (%)		 模型有效系数
E
模型校正结果 Calibration results (CK)
土壤贮水量
Soil water storage (mm)		 CK 195.93±5.73 199.83±5.41 9.6 0.65 23.36 11.9 0.56
开花期
Flowering stage (day of year)		 CK 128.33±1.40 130.33±1.15 1.6 0.99 2.16 1.7 —
成熟期
Maturity stage (day of year)		 CK 159.33±1.50 157.67±1.45 1.0 0.99 1.73 1.1 —
生物量
Biomass (Mg hm-2)		 CK 11.33±1.37 12.69±1.53 14.8 0.83 1.90 16.8 —
产量
Yield (Mg hm-2)		 CK 6.32±1.37 6.59±1.41 4.2 0.99 0.36 5.7 —
农田蒸散
ET_m2 (mm)		 CK 442.41±33.54 427.07±29.78 5.6 0.84 24.47 5.5 —
模型验证结果 Validation results (T1, T2, T3, T4)
土壤贮水量
Soil water strong (mm)		 T1 187.32±5.49 189.74±5.54 10.5 0.69 22.73 12.3 0.55
T2 186.45±5.66 197.18±5.28 15.1 0.69 30.35 16.3 0.24
T3 193.39±5.59 197.52±5.17 13.5 0.52 29.60 15.3 0.26
T4 190.80±5.08 204.67±4.87 15.3 0.54 32.31 15.2 0.27
开花期
Flowering stage (day of year)		 T1-T4 127.33±0.62 131.00±0.49 2.9 0.99 3.70 2.9 0.13
成熟期
Maturity stage (day of year)		 T1-T4 160.00±0.89 157.67±0.62 1.4 0.98 2.52 1.6 0.27
生物量
Biomass (Mg hm-2)		 T1-T4 11.98±1.53 12.66±1.02 8.6 0.67 1.18 9.9 0.36
产量
Yield (Mg hm-2)		 T1-T4 6.34±0.88 6.13±0.68 6.3 0.75 0.49 7.8 0.69
农田蒸散
ET_m2 (mm)		 T1-T4 410.63±23.89 416.21±31.54 6.6 0.67 29.64 7.2 0.40

图3

2016-2019年RZWQM-CERES模拟不同灌溉处理下动态生物量与实测值对比 缩写同表3。"

图4

2016-2019年RZWQM-CERES模拟不同灌溉处理收获期生物量和产量与实测值对比 缩写同表3。"

图5

2016-2019年RZWQM-CERES模拟不同灌溉处理农田蒸散(ET_S)与不考虑(或考虑)地下水补充的农田蒸散估算值ET_m1 (或ET_m2) (公式1)对比 缩写同表3。"

图6

不同降水年型下RZWQM-CERES模拟的冬小麦产量对灌溉量和灌溉次数的响应 子图标题中字母a为丰水年, b为平水年, c为枯水年; 数字1表示灌溉1次, 2表示灌溉2次, 3表示灌溉3次, 4表示灌溉4次, 5表示灌溉5次。灌溉处理中Rainfed表示雨养, T表示返青期灌溉, J表示拔节期灌溉, B表示孕穗期灌溉, F表示开花期灌溉, G表示灌浆期灌溉。"

图7

不同降水年型下RZWQM-CERES模拟的冬小麦水分利用效率(WUE)对灌溉量和灌溉次数的响应 子图标题中字母a为丰水年, b为平水年, c为枯水年; 数字1表示灌溉1次, 2表示灌溉2次, 3表示灌溉3次, 4表示灌溉4次, 5表示灌溉5次。灌溉处理中Rainfed表示雨养, T表示返青期灌溉, J表示拔节期灌溉, B表示孕穗期灌溉, F表示开花期灌溉, G表示灌浆期灌溉。"

图8

筛选的不同降水年型下最优灌溉量方案的冬小麦产量(Yield)和水分利用效率(WUE) 处理同图6。"

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